Almihyawi et al., 2025 - Google Patents
A secure smart monitoring network for hybrid energy systems using IoT, AIAlmihyawi et al., 2025
View HTML- Document ID
- 6531316563679072741
- Author
- Almihyawi A
- et al.
- Publication year
- Publication venue
- Discover Computing
External Links
Snippet
Energy systems are now incorporating Internet of Things technology to make better monitoring and management of energy possible. This research study analyzes the design and implementation of a secure and smart monitoring network for hybrid energy systems …
- 238000012544 monitoring process 0 title abstract description 73
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
- G06Q10/0639—Performance analysis
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
- H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ahmed et al. | Industrial Internet of Things enabled technologies, challenges, and future directions | |
| Arshi et al. | IoT in energy: a comprehensive review of technologies, applications, and future directions | |
| Almihyawi | A secure smart monitoring network for hybrid energy systems using IoT, AI | |
| US20180034701A1 (en) | Creating and managing dynamic internet of things policies | |
| Patel et al. | Modeling the Green Cloud Continuum: integrating energy considerations into Cloud–Edge models | |
| Al‐Atawi | Enhancing data management and real‐time decision making with IoT, cloud, and fog computing | |
| Jain et al. | AI-powered cost optimization in IoT: A systematic review of machine learning and predictive analytics in TCO reduction | |
| Alaguraj et al. | Integration of edge computing-enabled IoT monitoring and sharded blockchain in a renewable energy-based smart grid system | |
| Abubakar et al. | A survey on the integration of blockchain and IoT: challenges and opportunities | |
| EP4607319A1 (en) | Bi-directional electrical microgrid of networked processing-on-demand systems with improved communications processes | |
| Parekh et al. | A Review of IoT-Enabled Smart Energy Hub Systems: Rising, Applications, Challenges, and Future Prospects | |
| Kumar et al. | Implementation of microgrid digital twin system for unmanned vehicles with cloud computing techniques | |
| Zekiye et al. | Blockchain-based federated learning for decentralized energy management systems | |
| Hasan | Federated Learning Models for Privacy-Preserving AI In Enterprise Decision Systems | |
| Sena et al. | Edge computing in smart grids | |
| Computing | A secure smart monitoring network for hybrid energy systems using IoT, AI | |
| Mouzakitis et al. | Enhancing Decision Support Systems for the Energy Sector with Sustainable Artificial Intelligence Solutions | |
| Pene et al. | Edge intelligence in smart energy CPS | |
| Kak et al. | Energy minimization in a cloud computing environment | |
| Zeng et al. | Big Data in Smart Grid and Edge Computing of the IoT | |
| Goswami et al. | Applications of big data and Internet of Things in power system | |
| Khalif et al. | Smart Grid Data Management and Analytics Using Cloud Computing: Trends and Future Directions | |
| Hussain et al. | Computational viability of fog methodologies in IoT enabled smart city architectures-a smart grid case study | |
| Khan | A distributed computing architecture to enable advances in field operations and management of distributed infrastructure | |
| Elhajj et al. | Integrating IoT and blockchain for smart urban energy management: enhancing sustainability through real-time monitoring and optimization |